Literature DB >> 18073490

Ignoring intermarker linkage disequilibrium induces false-positive evidence of linkage for consanguineous pedigrees when genotype data is missing for any pedigree member.

Bingshan Li1, Suzanne M Leal.   

Abstract

Missing genotype data can increase false-positive evidence for linkage when either parametric or nonparametric analysis is carried out ignoring intermarker linkage disequilibrium (LD). Previously it was demonstrated by Huang et al. [1] that no bias occurs in this situation for affected sib-pairs with unrelated parents when either both parents are genotyped or genotype data is available for two additional unaffected siblings when parental genotypes are missing. However, this is not the case for autosomal recessive consanguineous pedigrees, where missing genotype data for any pedigree member within a consanguinity loop can increase false-positive evidence of linkage. False-positive evidence for linkage is further increased when cryptic consanguinity is present. The amount of false-positive evidence for linkage, and which family members aid in its reduction, is highly dependent on which family members are genotyped. When parental genotype data is available, the false-positive evidence for linkage is usually not as strong as when parental genotype data is unavailable. For a pedigree with an affected proband whose first-cousin parents have been genotyped, further reduction in the false-positive evidence of linkage can be obtained by including genotype data from additional affected siblings of the proband or genotype data from the proband's sibling-grandparents. For the situation, when parental genotypes are unavailable, false-positive evidence for linkage can be reduced by including genotype data from either unaffected siblings of the proband or the proband's married-in-grandparents in the analysis. (c) 2007 S. Karger AG, Basel

Entities:  

Mesh:

Year:  2007        PMID: 18073490      PMCID: PMC2798807          DOI: 10.1159/000112367

Source DB:  PubMed          Journal:  Hum Hered        ISSN: 0001-5652            Impact factor:   0.444


  26 in total

Review 1.  Genotyping for human whole-genome scans: past, present, and future.

Authors:  J L Weber; K W Broman
Journal:  Adv Genet       Date:  2001       Impact factor: 1.944

2.  Merlin--rapid analysis of dense genetic maps using sparse gene flow trees.

Authors:  Gonçalo R Abecasis; Stacey S Cherny; William O Cookson; Lon R Cardon
Journal:  Nat Genet       Date:  2001-12-03       Impact factor: 38.330

3.  Characteristics of genetic markers and maps for cost-effective genome screens using diallelic markers.

Authors:  Katrina A B Goddard; Ellen M Wijsman
Journal:  Genet Epidemiol       Date:  2002-03       Impact factor: 2.135

4.  Pitfalls in homozygosity mapping.

Authors:  M G Miano; S G Jacobson; A Carothers; I Hanson; P Teague; J Lovell; A V Cideciyan; N Haider; E M Stone; V C Sheffield; A F Wright
Journal:  Am J Hum Genet       Date:  2000-09-27       Impact factor: 11.025

5.  Caution on pedigree haplotype inference with software that assumes linkage equilibrium.

Authors:  Daniel J Schaid; Shannon K McDonnell; Liang Wang; Julie M Cunningham; Stephen N Thibodeau
Journal:  Am J Hum Genet       Date:  2002-10       Impact factor: 11.025

6.  Impact of parental relationships in maximum lod score affected sib-pair method.

Authors:  Anne-Louise Leutenegger; Emmanuelle Génin; Elizabeth A Thompson; Françoise Clerget-Darpoux
Journal:  Genet Epidemiol       Date:  2002-11       Impact factor: 2.135

7.  Estimation of the inbreeding coefficient through use of genomic data.

Authors:  Anne-Louise Leutenegger; Bernard Prum; Emmanuelle Génin; Christophe Verny; Arnaud Lemainque; Françoise Clerget-Darpoux; Elizabeth A Thompson
Journal:  Am J Hum Genet       Date:  2003-07-29       Impact factor: 11.025

8.  Large-scale genotyping of complex DNA.

Authors:  Giulia C Kennedy; Hajime Matsuzaki; Shoulian Dong; Wei-min Liu; Jing Huang; Guoying Liu; Xing Su; Manqiu Cao; Wenwei Chen; Jane Zhang; Weiwei Liu; Geoffrey Yang; Xiaojun Di; Thomas Ryder; Zhijun He; Urvashi Surti; Michael S Phillips; Michael T Boyce-Jacino; Stephen P A Fodor; Keith W Jones
Journal:  Nat Biotechnol       Date:  2003-09-07       Impact factor: 54.908

9.  Ignoring linkage disequilibrium among tightly linked markers induces false-positive evidence of linkage for affected sib pair analysis.

Authors:  Qiqing Huang; Sanjay Shete; Christopher I Amos
Journal:  Am J Hum Genet       Date:  2004-10-18       Impact factor: 11.025

10.  Linkage analysis and family classification under heterogeneity.

Authors:  J Ott
Journal:  Ann Hum Genet       Date:  1983-10       Impact factor: 1.670

View more
  4 in total

1.  Linkage analysis with dense SNP maps in isolated populations.

Authors:  Céline Bellenguez; Carole Ober; Catherine Bourgain
Journal:  Hum Hered       Date:  2009-04-09       Impact factor: 0.444

2.  Multiple subsampling of dense SNP data localizes disease genes with increased precision.

Authors:  William C L Stewart; Anna L Peljto; David A Greenberg
Journal:  Hum Hered       Date:  2009-12-18       Impact factor: 0.444

3.  Collapsed haplotype pattern method for linkage analysis of next-generation sequence data.

Authors:  Gao T Wang; Di Zhang; Biao Li; Hang Dai; Suzanne M Leal
Journal:  Eur J Hum Genet       Date:  2015-04-15       Impact factor: 4.246

4.  Novel loci interacting epistatically with bone morphogenetic protein receptor 2 cause familial pulmonary arterial hypertension.

Authors:  Laura Rodriguez-Murillo; Ryan Subaran; William C L Stewart; Sreemanta Pramanik; Sudhir Marathe; Robyn J Barst; Wendy K Chung; David A Greenberg
Journal:  J Heart Lung Transplant       Date:  2009-10-28       Impact factor: 10.247

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.